The main purpose of this work is to prepare self-emulsifying drug delivery system (SEDDS) of a poorly water soluble drug, puerarin. Solubility of puerarin was determined in various oils and surfactants. Oleic acid and Tween 80 provided higher solubility. Addition of propylene glycol as cosurfactant improved solubility of puerarin and the spontaneity of self-emulsification. A series of mixtures comprising oleic acid, propylene glycol and Tween 80 were prepared and their self-emulsifying properties were studied. Pseudo-ternary phase diagrams were constructed to identify the efficient self-emulsification region and particle sizes of the resultant emulsions were determined using a laser diffraction sizer. The harmacokinetic behaviors of three different SEDDS formulations (F2, F3, F4) were investigated in Beagle dogs. The bioavailability was compared using the pharmacokinetic parameters, peak plasma concentration (Cmax), time to reach peak plasma concentration (Tmax) and total area under the plasma concentration-time curve (AUC0-t). AUC0-t was significantly higher in formulation F2 group (5.201±0.511) ng·mL-1·h and formulation F3 group (5.174±0.498) ng·mL-1·h than that in formulation F4 group (3.013±0.623) ng·mL-1·h. Also, Cmax was significantly higher in formulation F2 group (1.524±0.125) ng·mL-1 and formulation F3 group (1.513±0.157) ng·mL-1 than that in formulation F4 group (0.939±0.089) ng·mL-1. Further analysis of the data showed a statistically significant difference between F2 and F4 (P<0.01) as well as F3 and F4 (P<0.01) with regard to the values of AUC0-∞ and Cmax for three SEDDS formulations, but not between those of F2 and F3 (P>0.05). From these studies, the SEDDS formulation containing oleic acid (17.5%), Tween 80 (34.5%) and propylene glycol (34.5%) (w/w) was selected as an optimized SEDDS formulation of puerarin. The data suggest the potential use of SEDDS to improve oral absorption of puerarin.

Objective To investigate the application of lymphocyte parameters in screening the lymphocyte proliferation and re-active hyperplasia disease.Methods 128 cases as the healthy control,100 cases of lymphoma,35 cases of multiple myeloma(MM), 34 cases of lymphocytes reactive hyperplasia(RL)and 5 cases of chronic lymphocytic leukemia(CLL)were selected and performed the peripheral blood cells analysis by the Sysmex XE-2100 hematology analyzer.The relevant lymphocyte parameter values were re-corded and the comparative analysis in the difference between the disease groups and the control group was performed.The role of each lymphocyte parameter in screening the lymphocyte proliferation and reactive hyperplasia diseases was evaluated by the receiver operating characteristic curve(ROC curve).Results The high fluorescence lymphocytes(HFL),in the control group was 0.008 ± 0.008,in the lymphoma group was 0.016±0.058,in the MM group was 0.019 ±0.063,in the RL group was 0.040 ±0.070,and CLL group was 0.388±0.158.Compared with control group,the difference of RL and CLL group was statistically significant(P <0.05).The percentage of lymphocytes(LY%,:the control group:34.4%±5.9%,the lymphoma group:26.6%±13.1%,the MM group:31.0%±13.1%,the RL group:29.2%±15.4% and the CLL group:44.5%±38.5%.The difference between the lympho-ma group and the control group was statistically significant(P <0.001).The lymphocytes structural parameters X(LY-X),the con-trol group:833.5 ± 22.7,the lymphoma group:867.9 ± 28.5,the MM group:867.9 ± 26.6,the RL group:859.2 ± 27.8 and the CLL group:894.0 ± 65.4.Except for the CLL group,the differences between other groups and control group were statistically significant(P <0.001).The lymphocytes structural parameters Y(LY-Y),the control group:659.6 ± 23.0,the lymphoma group:669.4 ± 43.5,the MM group:665.9 ± 37.1,the RL group:665.9 ± 40.0 and the CLL group:778.4 ± 152.1.Compared with the control group,the difference of the lymphoma group was statistically significant(P <0.05).AUC of the ROC curve in the pa-tients with lymphocyte proliferation and reactive hyperplasia disease by LY-X screening was 0.819,with the sensitivity of 80.5%and the specificity of 60.1% when cutoff value was 842.5.Conclusion The lymphocyte parameters,especially LY-X can reveal the
morphological changes of lymphocytes sensitively and contribute to screening the patients with lymphocyte proliferation and reactive hyperplasia disease.

Transfer learning is provided with potential research value and application prospect in motor imagery electroencephalography (MI-EEG)-based brain-computer interface (BCI) rehabilitation system, and the source domain classification model and transfer strategy are the two important aspects that directly affect the performance and transfer efficiency of the target domain model. Therefore, we propose a parameter transfer learning method based on shallow visual geometry group network (PTL-sVGG). First, Pearson correlation coefficient is used to screen the subjects of the source domain, and the short-time Fourier transform is performed on the MI-EEG data of each selected subject to acquire the time-frequency spectrogram images (TFSI). Then, the architecture of VGG-16 is simplified and the block design is carried out, and the modified sVGG model is pre-trained with TFSI of source domain. Furthermore, a block-based frozen-fine-tuning transfer strategy is designed to quickly find and freeze the block with the greatest contribution to sVGG model, and the remaining blocks are fine-tuned by using TFSI of target subjects to obtain the target domain classification model. Extensive experiments are conducted based on public MI-EEG datasets, the average recognition rate and Kappa value of PTL-sVGG are 94.9% and 0.898, respectively. The results show that the subjects' optimization is beneficial to improve the model performance in source domain, and the block-based transfer strategy can enhance the transfer efficiency, realizing the rapid and effective transfer of model parameters across subjects on the datasets with different number of channels. It is beneficial to reduce the calibration time of BCI system, which promote the application of BCI technology in rehabilitation engineering.
Algorithms ; Brain-Computer Interfaces ; Electroencephalography/methods* ; Humans ; Imagination ; Machine Learning

Objective To construct a predictive model for the severity of depression based on the expression of circular RNAs(circRNAs)in peripheral blood.Methods Selecting 80 patients with depression who visited our hospital from August 2022 to August 2023,they were divided into a mild to moderate group of 49 cases and a severe group of 31 cases.Forty healthy individuals were selected as the healthy group,and after gene chip screening,five circRNAs with significant differences were selected.Further analysis was conducted on the relationship between circRNAs and the severity of depression,and independent risk factors affecting the severity of depression were analyzed,based on the analysis results,construct a depression severity prediction model using a column chart based on the expression of circRNAs in peripheral blood.Results Compared with the healthy group and mild to moderate group,the severe group had circRNA_100679,circRNA_1 03636 relative expression level decreased,circRNA_102802,circRNA_103964,The relative expression level of circRNA_002143 increased(P＜0.05).CircRNA_100679,circRNA_103636 is negatively correlated with the severity of depression(r=-0.594,-0.512,P＜0.05),circRNA_102802,circRNA_103964,circRNA_002143 is positively correlated with the severity of depression(r=0.603,0.425,0.412,P＜0.05).CircRNA_100679,circRNA_102802,circRNA_103636,circRNA_103964,circRNA_002143,family history of mental illness,and 5-hydroxytryptamine(5-HT)are all risk factors for the severity of depression(P＜0.05).The predicted area under the curve of the column chart prediction model based on risk factors such as peripheral blood circRNAs is 0.900,with a 95％CI:0.811-0.945.The model has good discrimination and high internal validation consistency.Conclusion The construction of a column chart model based on circRNAs expression for predicting the severity of depression has good predictive value and can provide reference for the diagnosis and treatment of depression severity in clinical practice.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide and macrophage polarization plays an important role in its pathogenesis. However, which molecule regulates macrophage polarization in NAFLD remains unclear. Herein, we showed NAFLD mice exhibited increased 17β-hydroxysteroid dehydrogenase type 7 (17β-HSD7) expression in hepatic macrophages concomitantly with elevated M1 polarization. Single-cell RNA sequencing on hepatic non-parenchymal cells isolated from wild-type littermates and macrophage-17β-HSD7 knockout mice fed with high fat diet (HFD) for 6 weeks revealed that lipid metabolism pathways were notably changed. Furthermore, 17β-HSD7 deficiency in macrophages attenuated HFD-induced hepatic steatosis, insulin resistance and liver injury. Mechanistically, 17β-HSD7 triggered NLRP3 inflammasome activation by increasing free cholesterol content, thereby promoting M1 polarization of macrophages and the secretion of pro-inflammatory cytokines. In addition, to help demonstrate that 17β-HSD7 is a potential drug target for NAFLD, fenretinide was screened out from an FDA-approved drug library based on its 17β-HSD7 dehydrogenase inhibitory activity. Fenretinide dose-dependently abrogated macrophage polarization and pro-inflammatory cytokines production, and subsequently inhibited fat deposition in hepatocytes co-cultured with macrophages. In conclusion, our findings suggest that blockade of 17β-HSD7 signaling by fenretinide would be a drug repurposing strategy for NAFLD treatment.